单基因糖尿病遗传学研究进展:基因型–表型关联及精准诊疗新策略
Advances in Genetic Research on Monogenic Diabetes: Genotype-Phenotype Correlations and Novel Strategies for Precision Diagnosis and Treatment
DOI: 10.12677/jcpm.2026.54282, PDF,   
作者: 刘新宇:济宁医学院临床医学院,山东 济宁;张正军*:济宁医学院附属医院内分泌遗传代谢科,山东 济宁
关键词: 单基因糖尿病MODY新生儿糖尿病基因型–表型关联精准医学基因检测 Monogenic Diabetes MODY Neonatal Diabetes Mellitus Genotype-Phenotype Correlation Precision Medicine Genetic Testing
摘要: 单基因糖尿病(Monogenic Diabetes)是一类由单个基因变异导致的特殊类型糖尿病,其发病机制与传统1型糖尿病和2型糖尿病存在显著差异。随着高通量测序技术的发展,越来越多与单基因糖尿病相关的致病基因被发现,使疾病诊断逐渐从临床表型驱动向分子遗传学驱动转变。与此同时,不同基因变异不仅影响疾病的发生,还在一定程度上决定患者的临床表型特征、疾病进展速度以及对药物治疗的反应差异。近年来,基因型–表型关联研究不断深入,使得单基因糖尿病的疾病谱系逐渐清晰,也为精准诊疗策略的建立提供了重要理论基础。本文系统综述在于阐述单基因糖尿病的遗传学基础、主要致病基因、基因型–表型关联特征、分子诊断技术及精准治疗策略,并对未来研究方向进行相关的展望,以期为临床诊疗与基础研究提供参考依据。
Abstract: Monogenic diabetes is a distinct subtype of diabetes caused by mutations in a single gene, with pathogenic mechanisms that differ significantly from those of classical type 1 and type 2 diabetes. With the advancement of high-throughput sequencing technologies, an increasing number of causative genes associated with monogenic diabetes have been identified, gradually shifting the diagnostic paradigm from a clinical phenotype-driven approach to a molecular genetics-based one. Moreover, different genetic variants not only influence disease onset but also, to a certain extent, determine patients’ clinical phenotypic characteristics, the rate of disease progression, and differential responses to pharmacological therapy. In recent years, in-depth investigations into genotype-phenotype correlations have progressively clarified the disease spectrum of monogenic diabetes and have provided a crucial theoretical foundation for the development of precision diagnostic and therapeutic strategies. This review systematically summarizes the genetic basis of monogenic diabetes, major causative genes, genotype-phenotype correlation features, molecular diagnostic techniques, and precision treatment approaches, and also offers perspectives on future research directions, aiming to serve as a reference for clinical practice and basic research.
文章引用:刘新宇, 张正军. 单基因糖尿病遗传学研究进展:基因型–表型关联及精准诊疗新策略[J]. 临床个性化医学, 2026, 5(4): 553-565. https://doi.org/10.12677/jcpm.2026.54282

参考文献

[1] Zhang, H., Colclough, K., Gloyn, A.L. and Pollin, T.I. (2021) Monogenic Diabetes: A Gateway to Precision Medicine in Diabetes. Journal of Clinical Investigation, 131, e142244.
https://doi.org/10.1172/jci142244
[2] Horikawa, Y., Hosomichi, K. and Yabe, D. (2024) Monogenic Diabetes. Diabetology International, 15, 679-687.
https://doi.org/10.1007/s13340-024-00698-6
[3] Broome, D.T., Pantalone, K.M., Kashyap, S.R. and Philipson, L.H. (2020) Approach to the Patient with MODY-Monogenic Diabetes. The Journal of Clinical Endocrinology & Metabolism, 106, 237-250.
https://doi.org/10.1210/clinem/dgaa710
[4] Back, S.H. and Kaufman, R.J. (2012) Endoplasmic Reticulum Stress and Type 2 Diabetes. Annual Review of Biochemistry, 81, 767-793.
https://doi.org/10.1146/annurev-biochem-072909-095555
[5] Gersing, S., Hansen, T., Lindorff-Larsen, K. and Hartmann-Petersen, R. (2025) Glucokinase: From Allosteric Glucose Sensing to Disease Variants. Trends in Biochemical Sciences, 50, 255-266.
https://doi.org/10.1016/j.tibs.2024.12.007
[6] Hattersley, A.T. and Patel, K.A. (2017) Precision Diabetes: Learning from Monogenic Diabetes. Diabetologia, 60, 769-777.
https://doi.org/10.1007/s00125-017-4226-2
[7] Chaudhry, A., Thompson, D.M. and Chanoine, J. (2026) Diabetes Management in Maternally Inherited Diabetes and Deafness (MIDD): A Review and a Proposed Treatment Algorithm. Diabetes, Obesity and Metabolism, 28, 826-839.
https://doi.org/10.1111/dom.70240
[8] De Franco, E., Saint-Martin, C., Brusgaard, K., Knight Johnson, A.E., Aguilar-Bryan, L., Bowman, P., et al. (2020) Update of Variants Identified in the Pancreatic β-Cell K ATP Channel Genes KCNJ11 and ABCC8 in Individuals with Congenital Hyperinsulinism and Diabetes. Human Mutation, 41, 884-905.
https://doi.org/10.1002/humu.23995
[9] Abu Aqel, Y., Alnesf, A., Aigha, I.I., Islam, Z., Kolatkar, P.R., Teo, A., et al. (2024) Glucokinase (GCK) in Diabetes: From Molecular Mechanisms to Disease Pathogenesis. Cellular & Molecular Biology Letters, 29, Article No. 120.
https://doi.org/10.1186/s11658-024-00640-3
[10] Sternisha, S.M. and Miller, B.G. (2019) Molecular and Cellular Regulation of Human Glucokinase. Archives of Biochemistry and Biophysics, 663, 199-213.
https://doi.org/10.1016/j.abb.2019.01.011
[11] Liu, J., Xiao, X., Zhang, Q. and Yu, M. (2023) Insights from Basic Adjunctive Examinations of GCK-MODY, HNF1A-MODY, and Type 2 Diabetes: A Systemic Review and Meta-Analysis. Journal of Diabetes, 15, 519-531.
https://doi.org/10.1111/1753-0407.13390
[12] Ren, Q., Wang, Z., Yang, W., Han, X. and Ji, L. (2023) Maternal and Infant Outcomes in GCK-MODY Complicated by Pregnancy. The Journal of Clinical Endocrinology & Metabolism, 108, 2739-2746.
https://doi.org/10.1210/clinem/dgad188
[13] Timsit, J., Ciangura, C., Dubois-Laforgue, D., Saint-Martin, C. and Bellanne-Chantelot, C. (2021) Pregnancy in Women with Monogenic Diabetes Due to Pathogenic Variants of the Glucokinase Gene: Lessons and Challenges. Frontiers in Endocrinology, 12, Article 802423.
https://doi.org/10.3389/fendo.2021.802423
[14] Kirzhner, A., Barak, O., Vaisbuch, E., Zornitzki, T. and Schiller, T. (2022) The Challenges of Treating Glucokinase MODY during Pregnancy: A Review of Maternal and Fetal Outcomes. International Journal of Environmental Research and Public Health, 19, Article 5980.
https://doi.org/10.3390/ijerph19105980
[15] Haliyur, R., Tong, X., Sanyoura, M., Shrestha, S., Lindner, J., Saunders, D.C., et al. (2019) Human Islets Expressing HNF1A Variant Have Defective Β Cell Transcriptional Regulatory Networks. Journal of Clinical Investigation, 129, 246-251.
https://doi.org/10.1172/jci121994
[16] Qian, M.F., Bevacqua, R.J., Coykendall, V.M.N., Liu, X., Zhao, W., Chang, C.A., et al. (2023) HNF1α Maintains Pancreatic α and β Cell Functions in Primary Human Islets. JCI Insight, 8, e170884.
https://doi.org/10.1172/jci.insight.170884
[17] Low, B.S.J., Lim, C.S., Ding, S.S.L., Tan, Y.S., Ng, N.H.J., Krishnan, V.G., et al. (2021) Decreased GLUT2 and Glucose Uptake Contribute to Insulin Secretion Defects in MODY3/HNF1A HIPSC-Derived Mutant β Cells. Nature Communications, 12, Article No. 3133.
https://doi.org/10.1038/s41467-021-22843-4
[18] Ng, N.H.J., Ghosh, S., Bok, C.M., Ching, C., Low, B.S.J., Chen, J.T., et al. (2024) HNF4A and HNF1A Exhibit Tissue Specific Target Gene Regulation in Pancreatic Beta Cells and Hepatocytes. Nature Communications, 15, Article No. 4288.
https://doi.org/10.1038/s41467-024-48647-w
[19] Murphy, R., Colclough, K., Pollin, T.I., Ikle, J.M., Svalastoga, P., Maloney, K.A., et al. (2023) The Use of Precision Diagnostics for Monogenic Diabetes: A Systematic Review and Expert Opinion. Communications Medicine, 3, Article No. 136.
https://doi.org/10.1038/s43856-023-00369-8
[20] Miyachi, Y., Miyazawa, T. and Ogawa, Y. (2022) HNF1A Mutations and Beta Cell Dysfunction in Diabetes. International Journal of Molecular Sciences, 23, Article 3222.
https://doi.org/10.3390/ijms23063222
[21] Nkonge, K.M., Nkonge, D.K. and Nkonge, T.N. (2020) The Epidemiology, Molecular Pathogenesis, Diagnosis, and Treatment of Maturity-Onset Diabetes of the Young (MODY). Clinical Diabetes and Endocrinology, 6, Article No. 20.
https://doi.org/10.1186/s40842-020-00112-5
[22] Gϋemes, M., Rahman, S.A., Kapoor, R.R., Flanagan, S., Houghton, J.A.L., Misra, S., et al. (2020) Hyperinsulinemic Hypoglycemia in Children and Adolescents: Recent Advances in Understanding of Pathophysiology and Management. Reviews in Endocrine and Metabolic Disorders, 21, 577-597.
https://doi.org/10.1007/s11154-020-09548-7
[23] Clissold, R.L., Hamilton, A.J., Hattersley, A.T., Ellard, S. and Bingham, C. (2015) HNF1B-Associated Renal and Extra-Renal Disease—An Expanding Clinical Spectrum. Nature Reviews Nephrology, 11, 102-112.
https://doi.org/10.1038/nrneph.2014.232
[24] Peixoto-Barbosa, R., Reis, A.F. and Giuffrida, F.M.A. (2020) Update on Clinical Screening of Maturity-Onset Diabetes of the Young (MODY). Diabetology & Metabolic Syndrome, 12, Article No. 50.
https://doi.org/10.1186/s13098-020-00557-9
[25] Craven, M., Bamba, V., Calabria, A.C. and Pinney, S.E. (2025) Pediatric Hepatocyte Nuclear Factor 1B (HNF1B) Disease: Diabetes and Endocrine Manifestations. Pediatric Diabetes, 2025, Article 4077604.
https://doi.org/10.1155/pedi/4077604
[26] Zhang, Y., Sui, L., Du, Q., Haataja, L., Yin, Y., Viola, R., et al. (2024) Permanent Neonatal Diabetes-Causing Insulin Mutations Have Dominant Negative Effects on Beta Cell Identity. Molecular Metabolism, 80, Article 101879.
https://doi.org/10.1016/j.molmet.2024.101879
[27] Ashcroft, F.M. and Rorsman, P. (2013) KATP Channels and Islet Hormone Secretion: New Insights and Controversies. Nature Reviews Endocrinology, 9, 660-669.
https://doi.org/10.1038/nrendo.2013.166
[28] Pipatpolkai, T., Usher, S., Stansfeld, P.J. and Ashcroft, F.M. (2020) New Insights into KATP Channel Gene Mutations and Neonatal Diabetes Mellitus. Nature Reviews Endocrinology, 16, 378-393.
https://doi.org/10.1038/s41574-020-0351-y
[29] de Gouveia Buff Passone, C., Giani, E., Vaivre-Douret, L., Kariyawasam, D., Berdugo, M., Garcin, L., et al. (2022) Sulfonylurea for Improving Neurological Features in Neonatal Diabetes: A Systematic Review and Meta-Analyses. Pediatric Diabetes, 23, 675-692.
https://doi.org/10.1111/pedi.13376
[30] Wang, H., Saint-Martin, C., Xu, J., Ding, L., Wang, R., Feng, W., et al. (2020) Biological Behaviors of Mutant Proinsulin Contribute to the Phenotypic Spectrum of Diabetes Associated with Insulin Gene Mutations. Molecular and Cellular Endocrinology, 518, Article 111025.
https://doi.org/10.1016/j.mce.2020.111025
[31] Arunagiri, A., Alam, M., Haataja, L., Draz, H., Alasad, B., Samy, P., et al. (2024) Proinsulin Folding and Trafficking Defects Trigger a Common Pathological Disturbance of Endoplasmic Reticulum Homeostasis. Protein Science, 33, e4949.
https://doi.org/10.1002/pro.4949
[32] Greeley, S.A.W., Polak, M., Njølstad, P.R., Barbetti, F., Williams, R., Castano, L., et al. (2022) ISPAD Clinical Practice Consensus Guidelines 2022: The Diagnosis and Management of Monogenic Diabetes in Children and Adolescents. Pediatric Diabetes, 23, 1188-1211.
https://doi.org/10.1111/pedi.13426
[33] Pietrusiński, M., Grzybowska-Adamowicz, J., Płoszaj, T., Skoczylas, S., Borowiec, M., Piekarska, K., et al. (2025) The Clinical and Diagnostic Characterization of 6q24-Related Transient Neonatal Diabetes Mellitus: A Polish Pediatric Cohort Study. Biomedicines, 13, Article 2492.
https://doi.org/10.3390/biomedicines13102492
[34] Barbetti, F., Deeb, A. and Suzuki, S. (2024) Neonatal Diabetes Mellitus around the World: Update 2024. Journal of Diabetes Investigation, 15, 1711-1724.
https://doi.org/10.1111/jdi.14312
[35] Ibrahim, H., Balboa, D., Saarimäki-Vire, J., Montaser, H., Dyachok, O., Lund, P., et al. (2024) RFX6 Haploinsufficiency Predisposes to Diabetes through Impaired Beta Cell Function. Diabetologia, 67, 1642-1662.
https://doi.org/10.1007/s00125-024-06163-y
[36] Akiba, K., Zukeran, H., Hasegawa, Y. and Fukami, M. (2024) Initial Clinical Manifestations in a Young Male with RFX6-Variant-Associated Diabetes. Clinical Pediatric Endocrinology, 33, 224-228.
https://doi.org/10.1297/cpe.2024-0016
[37] Zmysłowska, A., Jakiel, P., Gadzalska, K., Majos, A., Płoszaj, T., Ben-Skowronek, I., et al. (2022) Next-Generation Sequencing Is an Effective Method for Diagnosing Patients with Different Forms of Monogenic Diabetes. Diabetes Research and Clinical Practice, 183, Article 109154.
https://doi.org/10.1016/j.diabres.2021.109154
[38] Lin, Y., Sheng, H., Ting, T.H., Xu, A., Yin, X., Cheng, J., et al. (2020) Molecular and Clinical Characteristics of Monogenic Diabetes Mellitus in Southern Chinese Children with Onset before 3 Years of Age. BMJ Open Diabetes Research & Care, 8, e001345.
https://doi.org/10.1136/bmjdrc-2020-001345
[39] Chung, W.K., Erion, K., Florez, J.C., Hattersley, A.T., Hivert, M., Lee, C.G., et al. (2020) Precision Medicine in Diabetes: A Consensus Report from the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetologia, 63, 1671-1693.
https://doi.org/10.1007/s00125-020-05181-w
[40] Tsoi, S.T.F., Lim, C.K.P., Ma, R.C.W., et al. (2025) Development of a Chinese-Specific Clinical Model to Predict Maturity-Onset Diabetes of the Young. Diabetes/Metabolism Research and Reviews, 41, e70087.
https://doi.org/10.1002/dmrr.70087
[41] Manders, T.R., Tan, C.A., Kobayashi, Y., Wahl, A., Araya, C., Colavin, A., et al. (2025) Harnessing Genotype and Phenotype Data for Population-Scale Variant Classification Using Large Language Models and Bayesian Inference. Human Genetics, 144, 605-614.
https://doi.org/10.1007/s00439-025-02743-z
[42] Bate, T.S.R., Huang, Y., Luo, X., Saunders, D.C., Walker, J.T., Rai, V., et al. (2026) RFX6 Expression Is Central to the Development and Function of the Neuroendocrine Compartments of the Pancreas and Intestine and Strongly Affects Diabetes Risk. Diabetology International, 17, Article No. 23.
https://doi.org/10.1007/s13340-025-00867-1
[43] Walker, J.T., Saunders, D.C., Rai, V., Chen, H., Orchard, P., Dai, C., et al. (2023) Genetic Risk Converges on Regulatory Networks Mediating Early Type 2 Diabetes. Nature, 624, 621-629.
https://doi.org/10.1038/s41586-023-06693-2
[44] Beydag-Tasöz, B.S., Yennek, S. and Grapin-Botton, A. (2023) Towards a Better Understanding of Diabetes Mellitus Using Organoid Models. Nature Reviews Endocrinology, 19, 232-248.
https://doi.org/10.1038/s41574-022-00797-x
[45] Bonnefond, A., Unnikrishnan, R., Doria, A., Vaxillaire, M., Kulkarni, R.N., Mohan, V., et al. (2023) Monogenic Diabetes. Nature Reviews Disease Primers, 9, Article No. 12.
https://doi.org/10.1038/s41572-023-00421-w
[46] Vasavada, R.C. and Dhawan, S. (2025) Harnessing Beta-Cell Replication: Advancing Molecular Insights to Regenerative Therapies in Diabetes. Frontiers in Endocrinology, 16, Article 1612576.
https://doi.org/10.3389/fendo.2025.1612576
[47] Lee, J. and Lee, J. (2022) Endoplasmic Reticulum (ER) Stress and Its Role in Pancreatic Β-Cell Dysfunction and Senescence in Type 2 Diabetes. International Journal of Molecular Sciences, 23, Article 4843.
https://doi.org/10.3390/ijms23094843
[48] Alemu, R., Sharew, N.T., Arsano, Y.Y., Ahmed, M., Tekola-Ayele, F., Mersha, T.B., et al. (2025) Multi-Omics Approaches for Understanding Gene-Environment Interactions in Noncommunicable Diseases: Techniques, Translation, and Equity Issues. Human Genomics, 19, Article No. 8.
https://doi.org/10.1186/s40246-025-00718-9
[49] Fasolino, M., Schwartz, G.W., Patil, A.R., Mongia, A., Golson, M.L., Wang, Y.J., et al. (2022) Single-Cell Multi-Omics Analysis of Human Pancreatic Islets Reveals Novel Cellular States in Type 1 Diabetes. Nature Metabolism, 4, 284-299.
https://doi.org/10.1038/s42255-022-00531-x
[50] Chen, K., Zhang, J., Huang, Y., Tian, X., Yang, Y. and Dong, A. (2022) Single-Cell RNA-Seq Transcriptomic Landscape of Human and Mouse Islets and Pathological Alterations of Diabetes. iScience, 25, Article 105366.
https://doi.org/10.1016/j.isci.2022.105366
[51] Naylor, R.N., Patel, K.A., Kettunen, J.L.T., Männistö, J.M.E., Støy, J., Beltrand, J., et al. (2024) Precision Treatment of Beta-Cell Monogenic Diabetes: A Systematic Review. Communications Medicine, 4, Article No. 145.
https://doi.org/10.1038/s43856-024-00556-1
[52] Yong, J., Johnson, J.D., Arvan, P., Han, J. and Kaufman, R.J. (2021) Therapeutic Opportunities for Pancreatic Β-Cell ER Stress in Diabetes Mellitus. Nature Reviews Endocrinology, 17, 455-467.
https://doi.org/10.1038/s41574-021-00510-4
[53] Russ-Silsby, J., Teles, M., Hassan, S.S., Elbarbary, N.S., Ngọc, C.T.B. and De Franco, E. (2025) Global Perspectives on Monogenic Forms of Diabetes. Diabetologia, 68, 2362-2373.
https://doi.org/10.1007/s00125-025-06495-3
[54] Rajpurkar, P., Chen, E., Banerjee, O. and Topol, E.J. (2022) AI in Health and Medicine. Nature Medicine, 28, 31-38.
https://doi.org/10.1038/s41591-021-01614-0
[55] Cheng, J., Novati, G., Pan, J., Bycroft, C., Žemgulytė, A., Applebaum, T., et al. (2023) Accurate Proteome-Wide Missense Variant Effect Prediction with Alphamissense. Science, 381, eadg7492.
https://doi.org/10.1126/science.adg7492
[56] Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., et al. (2021) Highly Accurate Protein Structure Prediction with AlphaFold. Nature, 596, 583-589.
https://doi.org/10.1038/s41586-021-03819-2